update model card README.md

README.md

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+---
+license: apache-2.0
+tags:
+- generated_from_trainer
+datasets:
+- sem_eval_2018_task_1
+metrics:
+- f1
+- accuracy
+model-index:
+- name: bert-finetuned-sem_eval-english
+  results:
+  - task:
+      name: Text Classification
+      type: text-classification
+    dataset:
+      name: sem_eval_2018_task_1
+      type: sem_eval_2018_task_1
+      config: subtask5.english
+      split: train
+      args: subtask5.english
+    metrics:
+    - name: F1
+      type: f1
+      value: 0.7113731269958242
+    - name: Accuracy
+      type: accuracy
+      value: 0.28103837471783294
+---
+
+<!-- This model card has been generated automatically according to the information the Trainer had access to. You
+should probably proofread and complete it, then remove this comment. -->
+
+# bert-finetuned-sem_eval-english
+
+This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the sem_eval_2018_task_1 dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.3131
+- F1: 0.7114
+- Roc Auc: 0.8046
+- Accuracy: 0.2810
+
+## Model description
+
+More information needed
+
+## Intended uses & limitations
+
+More information needed
+
+## Training and evaluation data
+
+More information needed
+
+## Training procedure
+
+### Training hyperparameters
+
+The following hyperparameters were used during training:
+- learning_rate: 2e-05
+- train_batch_size: 8
+- eval_batch_size: 8
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 5
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | F1     | Roc Auc | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:------:|:-------:|:--------:|
+| 0.4067        | 1.0   | 855  | 0.3205          | 0.6756 | 0.7766  | 0.2709   |
+| 0.2828        | 2.0   | 1710 | 0.3062          | 0.7058 | 0.7973  | 0.3014   |
+| 0.239         | 3.0   | 2565 | 0.3122          | 0.7100 | 0.8038  | 0.2810   |
+| 0.2145        | 4.0   | 3420 | 0.3131          | 0.7114 | 0.8046  | 0.2810   |
+| 0.1888        | 5.0   | 4275 | 0.3167          | 0.7096 | 0.8022  | 0.2844   |
+
+
+### Framework versions
+
+- Transformers 4.21.1
+- Pytorch 1.12.0+cu113
+- Datasets 2.4.0
+- Tokenizers 0.12.1